samples/APOLLO-2.txt

Clin Pharmacol Ther. 2019 Jul; 106(1): 52–57.  Published online 2019
Apr 29. doi: 10.1002/cpt.1425 PMCID: PMC6617989 PMID: 30838639

From
Discovery to Practice and Survivorship: Building a National Real‐World
Data Learning Healthcare Framework for Military and Veteran Cancer
Patients Jerry S. H. Lee,corresponding author 1 , 2 , 3 , 4 , 5 , 6
Kathleen M. Darcy, 4 , 7 , 8 Hai Hu, 9 Yovanni Casablanca, 7 , 8
Thomas P. Conrads, 10 Clifton L. Dalgard, 11 , 12 John B. Freymann, 13
Sean E. Hanlon, 5 Grant D. Huang, 6 Leonid Kvecher, 9 George
L. Maxwell, 10 Frank Meng, 14 , 15 Joel T. Moncur, 16 Clesson Turner,
17 Justin M. Wells, 18 Matthew D. Wilkerson, 4 , 11 , 12 Kangmin Zhu,
8 Rachel B. Ramoni, 6 and Craig D. Shriver corresponding author 8 , 19
Author information Article notes Copyright and License information
Disclaimer

The Applied Proteogenomics OrganizationaL Learning and Outcomes
(APOLLO) network is implementing a prospective curation and
translation of real‐world data (RWD) into real‐world evidence (RWE)
within the learning healthcare environment of the Department of
Defense and Department of Veterans Affairs. To support basic,
translational, clinical, and epidemiological sciences, APOLLO will
release data to public repositories for secondary analysis to assist
others in assessing whether similar molecular‐driven clinical practice
guidelines will improve health outcomes for their relevant cancer
populations.

In the United States, > 80% of patients with cancer are initially
diagnosed and treated in a community hospital setting rather than an
academic hospital setting. Despite the increased adoption of
electronic health records (EHRs), the lack of interoperable health
information systems makes it challenging to aggregate RWD generated
from a cancer patient’s journey before diagnosis, during treatment,
and throughout survivorship. RWD might include data collected as part
of routine health and cancer care delivery or for research
(translational, implementation science, and/or epidemiological)
efforts. Longitudinal collection of RWD is essential to generating RWE
and is often absent when elucidating long‐term consequences of care
strategies.

Recent studies have demonstrated the success of individualized cancer
care strategies enabled by molecular profiling and targeted
therapies. In the past 2 years, the US Food and Drug Administration
(FDA) has approved tumor site–agnostic, biomarker‐driven cancer
treatments and next‐generation sequencing in vitro diagnostic
devices.1 A parallel review process by the Center for Medicare &
Medicaid Services led to a national coverage determination
next‐generation sequencing‐based in vitro diagnostics. The rapid
development and approval of such technologies underscored this
widening gap in capturing real‐world use of molecular‐driven cancer
care to generate RWE to help inform regulatory and clinical
decisions.2

Conducting valid real‐world studies requires data quality assurance
through auditable data abstraction methods and incentives to drive
electronic capture of data during delivery of care.2 The Department of
Veterans Affairs (VA) has the nation's largest integrated healthcare
system with over 9 million veterans enrolled and is a high‐volume
provider of cancer care with nearly 50,000 incident cancer cases
reported in 2010.3 The VA Office of Research and Development has as
its three major priorities to: (i) enhance veteran access to multisite
clinical trials, (ii) make VA data a national resource, and (iii)
increase the real‐world impact of research findings. The VA Office of
Research and Development's national Cooperative Studies Program4 and
data resources enable researchers to access and identify initial
cohorts for further studies to advance RWD analysis have been
leveraged through partnerships with federal collaborators to further a
learning health care system within the VA. The Department of Defense
(DoD) Military Health System (MHS) is responsible for maintaining the
health and readiness of 1.7 million active‐duty and reserve service
members (SMs) and caring for 9.4 million beneficiaries in TRICARE
health benefit plans. The John P. Murtha Cancer Center at Uniformed
Services University and Walter Reed National Military Medical Center
offers a comprehensive cancer care operational view in 64 capability
areas to proactively mitigate and close gaps in cancer care and
research in the MHS. The John P. Murtha Cancer Center utilizes
agreements with other federal agencies and extramural collaborators to
provide return on investment by deploying the most robust and modern
molecular technologies under various programs. The administrative and
medical care data from both direct and indirect care are stored in the
military data repository, which includes detailed information on
demographics, diagnoses, diagnostic procedures, prescriptions,
ancillary and radiology services, treatments, cost of care, and vital
status. The DoD also has a cancer registry that collects detailed data
on cancer diagnosis and features, including some cancer
biomarkers. These RWD have been widely used for cancer research among
DoD beneficiaries.5, 6

Leveraging the two largest nationwide connected healthcare systems,
the APOLLO network was launched in 2016 with the intent of curating
longitudinal RWD and health outcome data to create and assess adoption
of new molecular‐driven clinical practice guidelines. By developing,
defining, and aligning RWD elements of MHS, patients with cancer from
prediagnosis through survivorship among the federal and civilian
partners, the APOLLO network is implementing an integrated
multifederal network for prospective curation and translation of RWD
into RWE in a learning healthcare environment that will assist other
payers in assessing whether similar clinical practice guidelines will
improve health outcomes for their relevant populations.

MOVING TOWARD RWD: LESSONS LEARNED AND ONGOING PILOTS TO BUILD
THE APOLLO ECOSYSTEM Previous large‐scale tumor characterization
projects, such as The Cancer Genome Atlas and the ongoing Clinical
Proteomics Tumor Analysis Consortium, focused on analyzing the
genomics and proteomics profile of tumors at a single time point.7 The
lack of focus on longitudinal RWD collection limits the clinical
utilization of these programs’ data.8 APOLLO is distinct from The
Cancer Genome Atlas and other previous tumor characterization projects
as it was focused on integrated proteogenomic analyses, the collection
of longitudinal RWD, and development of a sustainable collection
pipeline from its inception. The foundation of the approach is a
network of biospecimen collection sites throughout the DoD and VA plus
select civilian sites. APOLLO tissue collection is infused into
pathology departments to preserve patient care, optimize collections,
and control for preanalytic variables while involving the local
organizations as true partners. This culture of collaboration also
promotes the capture of longitudinal clinical, radiology imaging, and
patient data throughout patients’ disease cycles that can otherwise be
difficult to obtain. This culture expands to Clinical Laboratory
Improvement Amendment (CLIA) laboratories, biobanking, imaging
characterization, and proteogenomic analysis centers to form a robust
APOLLO ecosystem that will be leveraged to enable additional
longitudinal oncology studies of both established and new patients.

To maximize longitudinal clinical data collection, APOLLO uniquely
designed a combination of disease‐specific pilot retrospective studies
of hundreds of cases (APOLLOs 1–4) and prospective studies of ~ 8,000
cases (APOLLO 5). Successes and lessons learned during the
implementation of these pilot projects, as well as those from past
large‐scale molecular and clinical studies, are being leveraged to
successfully forge the APOLLO ecosystem. Central to generating RWE
from RWD in combination with molecular data is the challenge of
balancing effective biospecimen matching and integration of data from
multiple modalities from the same patient while maintaining accuracy
and privacy over time. One way the network tackled this issue was
bringing together early stakeholders to develop and adopt a
prospectively generated unique APOLLO participant and aliquot
identifiers (APOLLO ID; Figure 1). APOLLO ID will also be linked to a
128‐byte global unique participant and aliquot identifiers with an
“AP‐” prefix when data are uploaded to public repositories for
secondary analysis. The APOLLO system is electronically supported by
an enterprise informatics infrastructure, which includes a Data
Tracking System (DTS‐APOLLO) for transactional activities, a Data
Warehouse for Translational Research for (DW4TR‐APOLLO),9 and a
network of connected public data repositories to support capturing,
management, and delivery of RWD to the study team and the public to
enable discovery of RWE. Initial pilot datasets have been successfully
uploaded to the National Cancer Institute's Genomic Data Commons and
The Cancer Imaging Archive (TCIA) from both VA and DoD studies. The
length of patient follow‐up time within APOLLO will be pre‐estimated
for each cancer type using prior literature rather than by duration of
a funding cycle, so advanced planning will enable continued capturing
of such data from both the regulatory and technical perspectives.

An external file that holds a picture, illustration, etc.  Object name
is CPT-106-52-g001.jpg Figure 1 Applied Proteogenomics OrganizationaL
Learning and Outcomes (APOLLO) data ecosystem and workflow to enable
longitudinal real‐world data (RWD) collection and analysis. Clinical
activities are separated from research functions by a firewall so that
only de identified, limited datasets are available for research and
further, only safe‐harbor datasets are made publicly
available. Patient will be followed from the time of diagnosis through
remission and when disease recurs, for as long as possible. Tracking
of all such RWD is enabled by APOLLO IDs in a program‐wide Data
Tracking System for APOLLO (DTS‐APOLLO). Activities in molecular
center are tracked by local LIMS with metadata and higher‐level
molecular data tracked in DTS‐APOLLO. Transactional data in DTS‐APOLLO
will be quality assured and integrated in the Data Warehouse for
Translational Research for APOLLO (DW4TR‐APOLLO) for integrated
analysis to generate real‐world evidence (RWE), which will in turn
directly impact patient clinical services. Lower‐level raw molecular
and imaging data of very large size, on the other hand, will be
directly uploaded to public data repositories, including The Cancer
Imaging Archive (TCIA),11 Genomic Data Commons (GDC),12 and upcoming
Proteomic Data Commons (PDC) maintained by the National Cancer
Institute (NCI) following appropriate protocols and regulatory
procedures coordinated through DW4TR‐APOLLO. Such raw data, after
integration with the data in the DW4TR‐APOLLO enabled by APOLLO ID,
will become substrates for integrated research analysis for hypothesis
generation and testing, which will be the basis for the design of new
scientific experiments and clinical trials with results will
eventually impact future patient clinical care. Solid lines are for
clinical‐grade RWD and dotted lines for research‐grade RWD. DoD,
Department of Defense; EHR, electronic health record; VA, Veteran's
Affairs.

LOOKING AHEAD: INITIAL EFFORTS TO ELEVATE RWD TO RWE The APOLLO
program aspires to accelerate the application of next‐generation
proteogenomic profiling with deep baseline and longitudinal RWD from
DoD and VA EHRs and research records into RWE for FDA‐approved tests
and treatments for development and deployment of tools and strategies
used in the prevention, diagnosis, and treatment of cancer. These
activities support readiness and health by empowering patients and
providers to optimize their care and health through customized and
enterprise solutions. The program will deploy both retrospective and
prospective observational designs with provisions for clinical trial
participation. Select civilian cohorts with aggressive or rare cancers
will be incorporated with SMs and veterans to contribute diversity,
events, experiences, and outcomes to the disease‐oriented and
pan‐cancer cohorts to learn about, treat, and prevent cancers that
develop in warfighters.

Types of clinical and research RWD that will be collected by the
APOLLO network are listed in Table 1. This program will require and
utilize operationalized processes and procedures tracked via a
user‐friendly APOLLO Dashboard. Integrated analyses will incorporate a
deep complement of RWD from medical and research records. Sequencing
and proteomic data generated by CLIA facilities and analytical core
facilities will not only be analyzed using current clinical databases
but will be available for iterative reanalysis over time applying new
clinical databases and trusted sources to advance reinterpretation of
the patients’ molecular profiling data to determine future access to
new FDA‐approved drugs and/or clinical trial opportunities. This
program will provide data in support studies of basic science,
translational medicine, epidemiology, comparative effectiveness,
cost‐effectiveness, and health disparities. Various data‐release
provisions were incorporated into the APOLLO framework, including
release to repositories for future research, clinical trials,
indications and guidelines, dissemination to scientists, healthcare
professionals, and the public, release to study doctors when research
results meet guidelines for medical consideration for follow‐up and
clinical assessments, and return to patients when the research results
qualifies for release without clinical certification, as recommended
recently by the National Academies of Sciences, Engineering, and
Medicine.10

Table 1 Types of RWD from medical and research records for APOLLO

Captured into smart electronic clinical reporting and XML forms with
data dictionaries, valid value requirements, logging features, and
business rules. Data elements are labeled with a unique coded APOLLO
ID participant identifier.  Baseline data: Registration, eligibility,
consent, demographics, height, weight, risk factors, smoking status,
marital status, type of insurance, medical history, medications,
supplements, reproductive history, and family cancer history.
Surgical treatment: Surgical date, surgical procedures performed, AJCC
stage with edition details, and disease site–specific surgical
findings, including primary tumor size, disease distribution (location
and size pre/post surgery), residual disease status, military disease,
laterality, margins, redacted operative report(s), and comments.
Pathologic findings: Diagnosis date, definitive surgery date, ICD site
and behavior codes, detailed College of American Pathology electronic
cancer checklist13 with harmonized data dictionaries and conversion
between versions, redacted pathology reports, including cytologic
findings, clinical biomarker assessments, and other findings.
Case‐level data: Case organ type, lesion type, malignancy type,
primary site of diagnosis, ICD‐10 code, histology code, TNM edition
number, pathological group stage at diagnosis, CAP organ data creation
status, and biomarker creation status.  Research pathology
characterization: Baseline and in‐depth research pathology
characterization will be provided and compared with the clinical
diagnosis for tumor samples by expert pathologists and tissue imaging
researchers. The types of annotation may include tissue composition
details, clinical biomarker staining, and computer‐generated
annotation in imaged slides with intact tumor tissues or tissues
before and after laser microdissection.  Molecular data: Including
redacted report, primary findings, and secondary findings when
applicable from CLIA testing, clinical recommendations, clinical
actions taken and outcomes, and XML data from CLIA assays when
available implementing best practices and guidelines from the College
of American Pathology, American Society of Clinical Oncology, National
Comprehensive Cancer Network, and American College of Genetics and
Genomic for risk assessments, interpretation, certification, and
genetic counseling health conditions, including cancer.  DoD uses the
Illumina TruSight Tumor 15 tumor profiling assay with plans to deploy
the TruSight Oncology 500 tumor profiling DNA + RNA assay. VA uses the
Personalis AC CancerPlus DNA + RNA assay to evaluate 181 clinically
actionable genes or the PGDx Cancer Select 125 assay. Research
analytical facilities generate next generation sequencing and multiple
proteomic data. Immunoassay, cell‐free DNA, metabolomic, glycoprotein,
and lipidomic data may be available in subsets.  Clinical imaging: May
be acquired when accessible from medical records, imaging facilities,
and research records with regulatory approval and consent at a
baseline time point and as longitudinal series of collections to
monitor and document disease distribution patterns and features
utilizing enterprise solutions by the VA and customized solutions by
DoD programs in partnership with TCIA.  Baseline details regarding
imaging, including method, contrast, facility location, and dates for
acquisition, curation, and submissions to and receipt of annotation.11
Disease‐oriented features will be annotated by expert radiologists
using custom workstation configuration and standardized data
dictionary, including assessments of mass: laterality, calcifications,
thick septations, internal architecture; disease: presence,
calcification, locations, shape; ascites or effusion: volume;
lymphadenopathy: pathologic lymph nodes.  Computer‐generated features,
including but not limited to segmentation using machine learning and
artificial intelligence.  Pharmacologic therapies: Pharmacologic
therapy status by regimen, treatment line, or indication with
individual agent details with drug name, ICD‐O cancer site for
treatment, doses, route/delivery method, cycles, date first dose/start
date, date last dose/end date, dose schedule, active medication, dose
reduction, treatment selection (approved assay or an integral,
integrated, or exploratory biomarker), best response, and serious
adverse events.  FDA indication with companion diagnostic assays:
Non‐small cell lung cancer: Treat an EGFR exon 19 deletions or EGFR
exon 21 L858R alterations with afatinib, gefitinib, or erlotinib; an
EGFR exon 20 T790M alteration with osimertinib; ALK rearrangement with
alectinib, crizotinib, or ceritinib; BRAF V600E with dabrafenib and
trametinib. Melanoma: Treat BRAF V600E with dabrafenib or vemurafenib;
BRAF V600E or V600K with trametinib or cobimetinib with
vemurafenib. Breast cancer: Treat ERBB2/HER2 amplification with
trastuzumab, ado‐trastuzumab emtansine, or pertuzumab. Colorectal
cancer: Treat wild‐type KRAS (absence of mutations in codons 12 and
13) with cetuximab; wild‐type KRAS (absence of mutations in exons 2,
3, and 4) or wild‐type NRAS (absence of mutations in exons 2, 3, and
4) with panitumumab. Ovarian cancer: Treat BRCA1/2 alterations with
rucaparib. Treatment of adult and pediatric patients with cancer with
an NTRK fusion, including solid tumors and hematologic malignancies
with larotrectinib.  Radiotherapies: Radiotherapy status by location,
indication, radiation treatment line/regimen, laterality, field
treated, radiation site code (ICD‐O), start date, end date, number of
fractions, dose/fraction cGy, total dose cGy, best response, and best
response assessment method, and comments.  Outcome assessments: If
living: Disease status (alive with disease, no evidence of disease),
date of last visit or date last activity if different than visit and
capture individual dates of recurrence or progression with assessment
method(s) and additional details when available. If deceased: Date of
death and cause of death (cancer‐related, noncancer related, and
unknown), if other cause then specify. Clinical trial participation
will also be documented.  Epidemiologic data: May be provided directly
by patients or with research staff during interviews with patients
using a standardized data dictionary. Veterans may also contribute
data through the Million's Veterans Program.  Patient demographics,
including race, ethnicity, sex, marital status, education, employment,
and military service. Medical history regarding health conditions,
prior cancer diagnoses and treatments, height, and weight. Physical
activity for 12 months prior to the current diagnosis. Alcohol history
in entire life and currently. Tobacco products use in entire life and
currently. Work environment, including occupations, exposures, and
deployments. Family cancer history for blood relatives, including half
blood relatives. Reproductive history for women.  Patient‐reported
outcomes: Using validated instruments from trusted sources.  Patient
Reported Outcomes Measurements for Personalizing Treatment (PROMPT
Assessments): Quality of life using the 28‐item FACT‐G for physical,
social/family, emotional, and functional well‐being. Global health
using the 10‐item PROMIS Global Health version 1.2 instrument. Pain
and fatigue using the 3‐item PROMIS Pain 3a and the 4‐item PROMIS
Fatigue 4a instruments. Stress, anxiety, and depression combination
using the 10‐item NIH ToolBox Perceived Stress, 4‐item PROMIS Anxiety
4a, and 4‐item PROMIS Depression 4a instruments. Symptoms using the
4‐item FACT‐NTX‐4, the 4‐item PROMIS Cognitive Function 4a, and the
4‐item PROMIS Sleep Disturbance 4a instruments. Support for daily
living using the 11‐item PROMIS Instrumental Support version 2.0
instrument.  Focus assessments using validated instruments from
trusted sources and working to deploy novel surveys to address gaps
and support prevention, survivorship, palliative and end‐of‐life care
to strengthen cancer capabilities across the continuum from
prevention, early detection, treatment selection, mitigation of
effects, rehabilitation, and survivorship, including palliative and
end‐of‐life care. This may include assessments of barriers to care,
patient preferences regarding treatment and care, resilience, cancer
pain management, young adult survivorship, and serious adverse event
reporting.  Open in a separate window AJCC, American Joint Commission
on Cancer; ALK, anaplastic lymphoma kinase; APOLLO, Applied
Proteogenomics OrganizationaL Learning and Outcomes; BRAF, B‐type Raf;
BRCA, breast cancer; CAP, College of American Pathologists; cGy,
centigray; CLIA, Clinical Laboratory Improvement Amendment; DoD,
Department of Defense; EGFR, epidermal growth factor receptor; ERBB,
erythroblastic leukemia viral oncogene; FACT‐G, functional assessment
of cancer therapy general; FDA, US Food and Drug Administration; HER2,
human epidermal growth factor receptor 2; ICD‐10, International
Classification of Disease‐10th edition; ICD‐O, International
Classification of Disease for Oncology; KRAS, Kirsten RAt Sarcoma
virus; NTRK, Neurotrophic tropomyosin receptor kinase; PGDx, Personal
Genome Diagnostics; PROMIS, Patient‐Reported Outcomes Measurement
Information System; RWD, real‐world data; TCIA, The Cancer Imaging
Archive; TNM, Tumor, Node, Metastasis staging system; VA, Veteran's
Affairs.

Translation of RWD into RWE is a key component of APOLLO with
integrated systems for enhancing capabilities across the cancer care
continuum, driving efficiencies, and enhancing quality, thereby
improving health outcomes and the readiness of warfighters and the
operational medical force. The full potential of APOLLO will be
realized when interoperable EHRs are readily and securely exchangeable
across the DoD and VA with enterprise solutions and clinical decision
tools for molecular pathology, clinical imaging, patient‐reported
outcomes, clinical trials, serious adverse events reporting,
prevention clinics, rehabilitative and other supportive services, pain
management, survivorship, palliative care, end‐of‐life care, research,
and education.

RETURN ON INVESTMENT: LEVERAGING RWD AND RWE FOR DOD, VA, AND
THE GLOBAL CANCER ECOSYSTEM Improvements in readiness, health care,
and outcomes for SMs, veterans, health beneficiaries, and civilians
will be achieved not only from deliverables generated by the APOLLO
network but also from release of RWD and RWE to the public for
secondary research. APOLLO patients may also benefit from release of
research data that qualify either for clinical certification or direct
release based on criteria, such as level and quality of the
evidence. Federal agencies may also benefit from the generated
agreements, established working groups, and taskforces with
representation from the stakeholders and invited nonfederal experts,
aligned resources and assets, integrated and expanded infrastructure
and workforces, and the capabilities developed for APOLLO and
operationalized across the DoD and VA for implementing precision
oncology solutions to acquire and translate RWD from APOLLO into RWE
for SMs, veterans, and the global cancer ecosystem.

Funding Funding for these efforts was provided from Uniformed
Services University of the Health Sciences (USUHS) awards from the
Defense Health Program to the Murtha Cancer Center Research Program
(HU0001‐16‐2‐0014, C.D. Shriver and J.S.H. Lee), the Gynecologic
Cancer Center of Excellence (HU0001‐16‐2‐0006, Y. Casablanca and
G. Larry Maxwell), and HU0001‐16‐2‐004 (L. Kvecher and H. Hu)
administered by the Henry M. Jackson Foundation for the Advancement of
Military Medicine. This project has also been funded in whole or in
part with federal funds from the National Cancer Institute, National
Institutes of Health, under Contract No. HHSN261200800001E
(J.B. Freymann).

Conflict of Interest The authors declared no competing
interests for this work.

Disclaimer The contents of this publication are the sole
responsibility of the authors and do not necessarily reflect the
views, opinions, or policies of the USUHS, the Henry M. Jackson
Foundation for the Advancement of Military Medicine, Inc., the
Department of Defense (DoD), the Departments of the Army, Navy, or Air
Force, Department of Health and Human Services, or Department of
Veterans Affairs. Mention of trade names, commercial products, or
organization does not imply endorsement by the U.S. Government.

Acknowledgments The authors would like to thank Joseph Shaw,
Sara Sakura, Autumn Beemer Phillips, Gregory Samuel, Olga Castellanos,
Jillian Infusino, and Mayada Aljehani for their critical review of the
figure and paper.

Contributor Information Jerry S. H. Lee, Email:
ude.csu@yrrej.rd.

Craig D. Shriver, Email: lim.liam@vic.revirhs.d.giarc.

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